Marcus Hutter

发表

Robust inference of trees

Marco Zaffalon, Marcus Hutter, Marcus Hutter, 2005, Annals of Mathematics and Artificial Intelligence.

A Philosophical Treatise of Universal Induction pdf

Marcus Hutter, Samuel Rathmanner, Marcus Hutter, 2011, Entropy.

Predicting non-stationary processes

Marcus Hutter, Daniil Ryabko, 2008, Appl. Math. Lett..

Analytical Results on the BFS vs. DFS Algorithm Selection Problem: Part II: Graph Search

Marcus Hutter, Tom Everitt, Marcus Hutter, 2015, Australasian Conference on Artificial Intelligence.

Sparse Sequential Dirichlet Coding pdf

Joel Veness, Marcus Hutter, 2012, ArXiv.

Proceedings of the 9th European conference on Recent Advances in Reinforcement Learning

Scott Sanner, Marcus Hutter, 2011 .

On Thompson Sampling and Asymptotic Optimality

Laurent Orseau, Tor Lattimore, Marcus Hutter, 2017, IJCAI.

On Martin-Löf Convergence of Solomonoff's Mixture

Tor Lattimore, Marcus Hutter, Tor Lattimore, 2013, TAMC.

Rationality, optimism and guarantees in general reinforcement learning

Marcus Hutter, Peter Sunehag, Marcus Hutter, 2015, J. Mach. Learn. Res..

Editors' Introduction

Rocco A. Servedio, Marcus Hutter, Eiji Takimoto, 2007, ALT.

A Topological Approach to Meta-heuristics: Analytical Results on the BFS vs. DFS Algorithm Selection Problem pdf

Marcus Hutter, Tom Everitt, Marcus Hutter, 2015, ArXiv.

An Analytical Approach to the BFS vs. DFS Algorithm Selection Problem 1

Marcus Hutter, Tom Everitt, 2015 .

A Noise Tolerant Watershed Transformation with Viscous Force for Seeded Image Segmentation

Marcus Hutter, Stephen Gould, Di Yang, 2012, ACCV.

Solomonoff Induction Violates Nicod's Criterion

Marcus Hutter, Jan Leike, Marcus Hutter, 2015, ALT.

On the Foundations of Universal Sequence Prediction

Marcus Hutter, 2006, TAMC.

On the Possibility of Learning in Reactive Environments with Arbitrary Dependence pdf

Marcus Hutter, Daniil Ryabko, D. Ryabko, 2008, Theor. Comput. Sci..

MDL convergence speed for Bernoulli sequences

Marcus Hutter, Jan Poland, Marcus Hutter, 2006, Stat. Comput..

Online Learning of k-CNF Boolean Functions pdf

Laurent Orseau, Marc G. Bellemare, Joel Veness, 2015, IJCAI.

Pessimism About Unknown Unknowns Inspires Conservatism pdf

Marcus Hutter, Michael K. Cohen, 2020, COLT.

Agents in Known Probabilistics Environments

Marcus Hutter, Marcus Hutter, 2005 .

PAC Bounds for Discounted MDPs pdf

Tor Lattimore, Marcus Hutter, Tor Lattimore, 2012, ALT.

(Non-)Equivalence of Universal Priors

Marcus Hutter, Peter Sunehag, Ian Wood, 2013, Algorithmic Probability and Friends.

On Ensemble Techniques for AIXI Approximation

Joel Veness, Marcus Hutter, Peter Sunehag, 2012, AGI.

Algorithmic Learning Theory, 18th International Conference, ALT 2007, Sendai, Japan, October 1-4, 2007, Proceedings

Rocco A. Servedio, Marcus Hutter, Eiji Takimoto, 2007, ALT.

On Sequence Prediction for Arbitrary Measures

Marcus Hutter, Daniil Ryabko, 2007, 2007 IEEE International Symposium on Information Theory.

Universal sequential decisions in unknown environments

Marcus Hutter, 2001 .

Algorithmic Complexity

Marcus Hutter, Marcus Hutter, 1993 .

Universal Prediction of Selected Bits pdf

Tor Lattimore, Marcus Hutter, Vaibhav Gavane, 2011, ALT.

Defensive Universal Learning with Experts

Marcus Hutter, Jan Poland, Marcus Hutter, 2005, ALT.

On the Existence and Convergence of Computable Universal Priors

Marcus Hutter, Marcus Hutter, 2003, ALT.

General Loss Bounds for Universal Sequence Prediction

Marcus Hutter, 2001, ICML.

Featureless 2D–3D pose estimation by minimising an illumination-invariant loss

Marcus Hutter, Nathan Brewer, Srimal Jayawardena, 2010, 2010 25th International Conference of Image and Vision Computing New Zealand.

A Bayesian Review of the Poisson-Dirichlet Process pdf

Marcus Hutter, Wray L. Buntine, Marcus Hutter, 2010, ArXiv.

Algorithmic Randomness as Foundation of Inductive Reasoning and Artificial Intelligence pdf

Marcus Hutter, Marcus Hutter, 2011, ArXiv.

Proc. 3rd Conference on Artificial General Intelligence

Marcus Hutter, Emanuel Kitzelmann, Eric Baum, 2010 .

The Universal Algorithmic Agent AIXI

Marcus Hutter, 2005 .

Convergence and Loss Bounds for

Marcus Hutter, Bayesian Sequence Prediction, Marcus Hutter, 2003 .

Using Localization and Factorization to Reduce the Complexity of Reinforcement Learning

Marcus Hutter, Peter Sunehag, 2015, AGI.

Kolmogorov Complexity and Applications

Marcus Hutter, Wolfgang Merkle, Paul M. B. Vitányi, 2006 .

Tests of Machine Intelligence

Shane Legg, Marcus Hutter, 2006, 50 Years of Artificial Intelligence.

Predictive Hypothesis Identification pdf

Marcus Hutter, 2008, ArXiv.

Hybrid rounding techniques for knapsack problems

Marcus Hutter, Monaldo Mastrolilli, 2006, Discret. Appl. Math..

Universal Learning Theory

Marcus Hutter, 2010, Encyclopedia of Machine Learning.

On Representing (Anti)Symmetric Functions pdf

Marcus Hutter, Marcus Hutter, 2020, ArXiv.

Unifying probability and logic for learning

Marcus Hutter, John W. Lloyd, William T. B. Uther, 2013, IJCAI 2013.

Strong Asymptotic Assertions for Discrete MDL in Regression and Classification pdf

Marcus Hutter, Jan Poland, 2005, ArXiv.

Bayesian Regression of Piecewise Constant Functions pdf

Marcus Hutter, Marcus Hutter, 2006, ArXiv.

Foundations of Induction

Marcus Hutter, Marcus Hutter, 2011 .

Algorithmic Learning Theory, 21st International Conference, ALT 2010, Canberra, Australia, October 6-8, 2010. Proceedings

Frank Stephan, Thomas Zeugmann, Vladimir Vovk, 2010, ALT.

On the Computability of Solomonoff Induction and Knowledge-Seeking pdf

Marcus Hutter, Jan Leike, Marcus Hutter, 2015, ALT.

On Generalized Computable Universal Priors and their Convergence pdf

Marcus Hutter, 2006, Theor. Comput. Sci..

Distribution of mutual information from complete and incomplete data

Marco Zaffalon, Marcus Hutter, Marcus Hutter, 2004, Comput. Stat. Data Anal..

A New Local Distance-Based Outlier Detection Approach for Scattered Real-World Data pdf

Ke Zhang, Huidong Jin, Marcus Hutter, 2009, PAKDD.

A Game-Theoretic Analysis of the Off-Switch Game

Marcus Hutter, Tom Everitt, Elliot Catt, 2017, AGI.

Principles of Solomonoff Induction and AIXI pdf

Marcus Hutter, Peter Sunehag, Marcus Hutter, 2011, Algorithmic Probability and Friends.

Foundations of Machine Learning

Marcus Hutter, 2008 .

Ergodic MDPs Admit Self-Optimising Policies

Shane Legg, Marcus Hutter, 2004 .

Near-optimal PAC bounds for discounted MDPs

Tor Lattimore, Marcus Hutter, Tor Lattimore, 2014, Theor. Comput. Sci..

Exact Reduction of Huge Action Spaces in General Reinforcement Learning pdf

Marcus Hutter, Sultan Javed Majeed, Marcus Hutter, 2020, AAAI.

Offline to Online Conversion

Marcus Hutter, 2014, ALT.

Online Learning in Contextual Bandits using Gated Linear Networks pdf

Joel Veness, Marcus Hutter, Jianan Wang, 2020, NeurIPS.

Open Problems in Universal Induction & Intelligence pdf

Marcus Hutter, Marcus Hutter, 2009, Algorithms.

Statistical Machine Learning

Marcus Hutter, Marcus Hutter, 2009 .

Metric State Space Reinforcement Learning for a Vision-Capable Mobile Robot pdf

Jürgen Schmidhuber, Marcus Hutter, Faustino J. Gomez, 2006, IAS.

Complexity Monotone in Conditions and Future Prediction Errors

Jürgen Schmidhuber, Marcus Hutter, Alexey V. Chernov, 2006, Kolmogorov Complexity and Applications.

Learning in Reactive Environments with Arbitrary Dependence

Marcus Hutter, Daniil Ryabko, D. Ryabko, 2006, Kolmogorov Complexity and Applications.

Important Environmental Classes

Marcus Hutter, 2005 .

Sequence Prediction Based on Monotone Complexity

Marcus Hutter, 2003, COLT.

Reinforcement Learning via AIXI Approximation pdf

Joel Veness, Marcus Hutter, David Silver, 2010, AAAI.

Feature Markov Decision Processes pdf

Marcus Hutter, Marcus Hutter, 2008, ArXiv.

Practical robust estimators for the imprecise Dirichlet model

Marcus Hutter, 2009, Int. J. Approx. Reason..

Algorithmic Information Theory

Marcus Hutter, Marcus Hutter, G. Chaitin, 1977, IBM J. Res. Dev..

Preface [to] Theoretical Computer Science, Vol. 410 (19)

Rocco A. Servedio, Marcus Hutter, 2009 .

Robust Feature Selection by Mutual Information Distributions

Marco Zaffalon, Marcus Hutter, Marcus Hutter, 2002, UAI.

Concentration and Confidence for Discrete Bayesian Sequence Predictors

Tor Lattimore, Marcus Hutter, Peter Sunehag, 2013, ALT.

The Fastest and Shortest Algorithm for all Well-Defined Problems

Marcus Hutter, 2002, Int. J. Found. Comput. Sci..

Monotone Conditional Complexity Bounds on Future Prediction Errors

Marcus Hutter, Alexey V. Chernov, 2005, ALT.

Universal Learning Theory

Marcus Hutter, 2017, Encyclopedia of Machine Learning and Data Mining.

Universal Convergence of Semimeasures on Individual Random Sequences

Marcus Hutter, Andrej Muchnik, 2004, ALT.

Strong Asymptotic Optimality in General Environments pdf

Marcus Hutter, Michael K. Cohen, Elliot Catt, 2019, ArXiv.

Master Algorithms for Active Experts Problems based on Increasing Loss Values pdf

Marcus Hutter, Jan Poland, Marcus Hutter, 2005, ArXiv.

Feature Reinforcement Learning using Looping Suffix Trees

Marcus Hutter, Peter Sunehag, Mayank Daswani, 2012, EWRL.

Proceedings of the 18th international conference on Algorithmic Learning Theory

Rocco A. Servedio, Marcus Hutter, Eiji Takimoto, 2007 .

Loss Bounds and Time Complexity for Speed Priors pdf

Marcus Hutter, Jan Leike, Daniel Filan, 2016, AISTATS.

An integrated Bayesian analysis of LOH and copy number data

Marcus Hutter, Francesco Bertoni, Ivo Kwee, 2010, BMC Bioinformatics.

Fairness without Regret pdf

Marcus Hutter, Marcus Hutter, 2019, ArXiv.

Kolmogorov Complexity and Applications, 29.01. - 03.02.2006

Marcus Hutter, Paul M. B. Vitányi, Wolfgang Merkle, 2006, Kolmogorov Complexity and Applications.

Reward tampering problems and solutions in reinforcement learning: a causal influence diagram perspective pdf

Marcus Hutter, Tom Everitt, Marcus Hutter, 2019, Synthese.

Optimal Sequential Decisions based on Algorithmic Probability

Marcus Hutter, 2003, ArXiv.

Editors' Introduction

Frank Stephan, Thomas Zeugmann, Vladimir Vovk, 2010, ALT.

Asymptotically Optimal Agents

Tor Lattimore, Marcus Hutter, Tor Lattimore, 2011, ALT.

Context Tree Switching

Joel Veness, Michael H. Bowling, Marcus Hutter, 2011, 2012 Data Compression Conference.

A Combinatorial Perspective on Transfer Learning pdf

Joel Veness, Marcus Hutter, Jianan Wang, 2020, NeurIPS.

Fast Non-Parametric Bayesian Inference on Infinite Trees pdf

Marcus Hutter, Marcus Hutter, 2004, AISTATS.

Guest Editors' foreword

Frank Stephan, Thomas Zeugmann, Vladimir Vovk, 2013, Theor. Comput. Sci..

Robust Estimators under the Imprecise Dirichlet Model

Marcus Hutter, 2003, ISIPTA.

Asymptotics of discrete MDL for online prediction

Marcus Hutter, Jan Poland, Marcus Hutter, 2005, IEEE Transactions on Information Theory.

Conditions on Features for Temporal Difference-Like Methods to Converge pdf

Marcus Hutter, Sultan Javed Majeed, Samuel Yang-Zhao, 2019, IJCAI.

Proceedings of the Second Conference on Artificial General Intelligence

Ben Goertzel, Pascal Hitzler, Marcus Hutter, 2009 .

Algorithmic probability

Shane Legg, Marcus Hutter, Paul M. B. Vitányi, 2007, Scholarpedia.

Universal Reinforcement Learning Algorithms: Survey and Experiments

Marcus Hutter, John Aslanides, Jan Leike, 2017, IJCAI.

Temporal Difference Updating without a Learning Rate

Shane Legg, Marcus Hutter, S. Legg, 2007, NIPS.

3D Model Assisted Image Segmentation

Marcus Hutter, Di Yang, Srimal Jayawardena, 2011, 2011 International Conference on Digital Image Computing: Techniques and Applications.

Adaptive Context Tree Weighting

Marcus Hutter, Peter Sunehag, Wen Shao, 2012, 2012 Data Compression Conference.

Bayesian Treatment of Incomplete Discrete Data applied to Mutual Information and Feature Selection

Marco Zaffalon, Marcus Hutter, Marcus Hutter, 2003, KI.

Sequential Predictions based on Algorithmic Complexity

Marcus Hutter, 2006, J. Comput. Syst. Sci..

Logarithmic Pruning is All You Need pdf

Laurent Orseau, Marcus Hutter, Omar Rivasplata, 2020, NeurIPS.

Sequence prediction for non-stationary processes

Marcus Hutter, Daniil Ryabko, 2006, Combinatorial and Algorithmic Foundations of Pattern and Association Discovery.

Discriminative Hierarchical Rank Pooling for Activity Recognition

Marcus Hutter, Basura Fernando, Stephen Gould, 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Time Consistent Discounting pdf

Tor Lattimore, Marcus Hutter, Tor Lattimore, 2011, ALT.

Convergence and Error Bounds for Universal Prediction of Nonbinary Sequences

Marcus Hutter, 2001, ECML.

Asymptotically Unambitious Artificial General Intelligence pdf

Marcus Hutter, Michael K Cohen, Badri Vellambi, 2019, AAAI.

Gated Linear Networks pdf

Tor Lattimore, Joel Veness, Marcus Hutter, 2019, ArXiv.

The Loss Rank Principle for Model Selection pdf

Marcus Hutter, 2007, COLT.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics: Preface

Rocco A. Servedio, Marcus Hutter, Eiji Takimoto, 2007 .

Gradient-based Reinforcement Planning in Policy-Search Methods

Jürgen Schmidhuber, Marcus Hutter, Ivo Kwee, 2001, ArXiv.

Reflective Features Detection and Hierarchical Reflections Separation in Image Sequences

Marcus Hutter, Stephen Gould, Di Yang, 2014, 2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA).

Q-learning for history-based reinforcement learning

Marcus Hutter, Peter Sunehag, Mayank Daswani, 2013, ACML.

Reinforcement Learning (Dagstuhl Seminar 13321)

Laurent Orseau, Peter Auer, Marcus Hutter, 2013, Dagstuhl Reports.

Convergence of Discrete MDL for Sequential Prediction

Marcus Hutter, Jan Poland, 2004, COLT.

Context Tree Maximizing

Marcus Hutter, Peter Sunehag, Phuong Minh Nguyen, 2012, AAAI.

Short Tour Through the Book

Marcus Hutter, 2005 .

Convergence and Loss Bounds for Bayesian Sequence Prediction

Marcus Hutter, 2003, IEEE Trans. Inf. Theory.

Coding of Non-Stationary Sources as a Foundation for Detecting Change Points and Outliers in Binary Time-Series

Marcus Hutter, Peter Sunehag, Wen Shao, 2012, AusDM.

Sequential Extensions of Causal and Evidential Decision Theory

Marcus Hutter, Tom Everitt, Jan Leike, 2015, ADT.

AGI Safety Literature Review pdf

Marcus Hutter, Tom Everitt, Gary Lea, 2018, IJCAI.

Analytical Results on the BFS vs. DFS Algorithm Selection Problem. Part I: Tree Search

Marcus Hutter, Tom Everitt, Marcus Hutter, 2015, Australasian Conference on Artificial Intelligence.

Algorithmic complexity bounds on future prediction errors pdf

Jürgen Schmidhuber, Marcus Hutter, Alexey V. Chernov, 2007, Inf. Comput..

Bayesian Joint Estimation of CN and LOH Aberrations

Marcus Hutter, Francesco Bertoni, Ivo Kwee, 2009, IWANN.

Performance Guarantees for Homomorphisms Beyond Markov Decision Processes pdf

Marcus Hutter, Sultan Javed Majeed, 2019, AAAI.

Avoiding Wireheading with Value Reinforcement Learning pdf

Marcus Hutter, Tom Everitt, Marcus Hutter, 2016, AGI.

Prediction with Expert Advice by Following the Perturbed Leader for General Weights

Marcus Hutter, Jan Poland, Marcus Hutter, 2004, ALT.

On Martin-Löf (non-)convergence of Solomonoff's universal mixture

Tor Lattimore, Marcus Hutter, Tor Lattimore, 2015, Theor. Comput. Sci..

On the Convergence Speed of MDL Predictions for Bernoulli Sequences

Marcus Hutter, Jan Poland, 2004, ALT.

Consistency of Feature Markov Processes

Marcus Hutter, Peter Sunehag, Marcus Hutter, 2010, ALT.

An Open Problem Regarding the Convergence of Universal A Priori Probability

Marcus Hutter, 2003, COLT.

A Collection of Definitions of Intelligence

Shane Legg, Marcus Hutter, S. Legg, 2007, AGI.

Optimality of Universal Bayesian Sequence Prediction for General Loss and Alphabet

Marcus Hutter, Marcus Hutter, 2003, J. Mach. Learn. Res..

Model selection with the Loss Rank Principle pdf

Marcus Hutter, Minh-Ngoc Tran, 2010, Comput. Stat. Data Anal..

Extreme State Aggregation beyond MDPs

Marcus Hutter, Marcus Hutter, 2014, ALT.

The Sample-Complexity of General Reinforcement Learning

Tor Lattimore, Marcus Hutter, Peter Sunehag, 2013, ICML.

Recent Advances in Reinforcement Learning - 9th European Workshop, EWRL 2011.

Scott Sanner, Marcus Hutter, 2012 .

Thompson Sampling is Asymptotically Optimal in General Environments pdf

Laurent Orseau, Tor Lattimore, Marcus Hutter, 2016, UAI.

General Discounting Versus Average Reward

Marcus Hutter, 2006, ALT.

Distribution of Mutual Information

Marcus Hutter, Marcus Hutter, 2001, NIPS.

New Error Bounds for Solomonoff Prediction

Marcus Hutter, 2001, J. Comput. Syst. Sci..

Free Lunch for optimisation under the universal distribution

Tor Lattimore, Marcus Hutter, Tom Everitt, 2014, 2014 IEEE Congress on Evolutionary Computation (CEC).

Model Selection by Loss Rank for Classification and Unsupervised Learning

Marcus Hutter, Minh-Ngoc Tran, Marcus Hutter, 2010, 1011.1379.

Method For Recognising An Activity In A Sequence Of Images

Marcus Hutter, Stephen Gould, Peter Anderson, 2019 .

A Novel Illumination-Invariant Loss for Monocular 3D Pose Estimation

Marcus Hutter, Nathan Brewer, Srimal Jayawardena, 2011, 2011 International Conference on Digital Image Computing: Techniques and Applications.

Bayesian Reinforcement Learning with Exploration

Tor Lattimore, Marcus Hutter, Tor Lattimore, 2014, ALT.

Towards a Universal Theory of Artificial Intelligence Based on Algorithmic Probability and Sequential Decisions

Marcus Hutter, Marcus Hutter, 2000, ECML.

Fitness uniform optimization

Shane Legg, Marcus Hutter, S. Legg, 2006, IEEE Transactions on Evolutionary Computation.

Feature Reinforcement Learning in Practice pdf

Marcus Hutter, Peter Sunehag, Phuong Minh Nguyen, 2011, EWRL.

A Dual Process Theory of Optimistic Cognition

Marcus Hutter, Peter Sunehag, Marcus Hutter, 2014, CogSci.

Recent Advances in Reinforcement Learning

Scott Sanner, Marcus Hutter, Marcus Hutter, 2011, Lecture Notes in Computer Science.

A Monte-Carlo AIXI Approximation pdf

Joel Veness, Marcus Hutter, David Silver, 2009, J. Artif. Intell. Res..

Limits of Learning about a Categorical Latent Variable under Prior Near-Ignorance pdf

Marco Zaffalon, Marcus Hutter, Alberto Piatti, 2007, Int. J. Approx. Reason..

Convergence of Binarized Context-tree Weighting for Estimating Distributions of Stationary Sources

Marcus Hutter, Badri N. Vellambi, 2018, 2018 IEEE International Symposium on Information Theory (ISIT).

On the computability of Solomonoff induction and AIXI

Marcus Hutter, Jan Leike, Marcus Hutter, 2017, Theor. Comput. Sci..

Learning Agents with Evolving Hypothesis Classes

Marcus Hutter, Peter Sunehag, Marcus Hutter, 2013, AGI.

Can we measure the difficulty of an optimization problem?

Tansu Alpcan, Marcus Hutter, Tom Everitt, 2014, 2014 IEEE Information Theory Workshop (ITW 2014).

Bayesian DNA copy number analysis

Marcus Hutter, Francesco Bertoni, Ivo Kwee, 2009, BMC Bioinformatics.

Fitness uniform selection to preserve genetic diversity

Marcus Hutter, Marcus Hutter, 2001, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

Universal Sequence Prediction

Marcus Hutter, 2005 .

Fitness uniform deletion: a simple way to preserve diversity

Shane Legg, Marcus Hutter, S. Legg, 2005, GECCO '05.

Death and Suicide in Universal Artificial Intelligence

Marcus Hutter, Tom Everitt, Jarryd Martin, 2016, AGI.

Optimistic AIXI

Marcus Hutter, Peter Sunehag, Marcus Hutter, 2012, AGI.

Tractability of batch to sequential conversion

Marcus Hutter, 2018, Theor. Comput. Sci..

Optimistic Agents Are Asymptotically Optimal

Marcus Hutter, Peter Sunehag, 2012, Australasian Conference on Artificial Intelligence.

Can Intelligence Explode? pdf

Marcus Hutter, Marcus Hutter, 2012, ArXiv.

General time consistent discounting

Tor Lattimore, Marcus Hutter, Tor Lattimore, 2014, Theor. Comput. Sci..

To create a super-intelligent machine, start with an equation

Marcus Hutter, 2013 .

Discrete MDL Predicts in Total Variation

Marcus Hutter, Marcus Hutter, 2009, NIPS.

Market-Based Reinforcement Learning in Partially Observable Worlds

Jürgen Schmidhuber, Marcus Hutter, Ivo Kwee, 2001, ICANN.

On Q-learning Convergence for Non-Markov Decision Processes

Marcus Hutter, Sultan Javed Majeed, Marcus Hutter, 2018, IJCAI.

Universal Algorithmic Intelligence: A Mathematical Top→Down Approach pdf

Marcus Hutter, Marcus Hutter, 2007, Artificial General Intelligence.

A Taxonomy for Abstract Environments.

Shane Legg, Marcus Hutter, S. Legg, 2004 .

Universal Learning of Repeated Matrix Games pdf

Marcus Hutter, Jan Poland, Marcus Hutter, 2005, ArXiv.

Universal Artificial Intellegence - Sequential Decisions Based on Algorithmic Probability

Marcus Hutter, Marcus Hutter, 2005, Texts in Theoretical Computer Science. An EATCS Series.

Report on the Third Conference on Artificial General Intelligence

Ben Goertzel, Marcus Hutter, 2010, AI Mag..

Bad Universal Priors and Notions of Optimality

Marcus Hutter, Jan Leike, 2015, COLT.

Context tree maximizing reinforcement learning

Marcus Hutter, Peter Sunehag, Phuong Nguyen, 2012, AAAI 2012.

Generalised Discount Functions applied to a Monte-Carlo AI u Implementation pdf

Marcus Hutter, John Aslanides, Jan Leike, 2017, AAMAS.

How to Predict with Bayes, MDL, and Experts

Marcus Hutter, Marcus Hutter, 2005 .

Asymptotic Learnability of Reinforcement Problems with Arbitrary Dependence

Marcus Hutter, Daniil Ryabko, D. Ryabko, 2006, ALT.

A Theory of Universal Artificial Intelligence based on Algorithmic Complexity

Marcus Hutter, Marcus Hutter, 2000, ArXiv.

Self-Optimizing and Pareto-Optimal Policies in General Environments based on Bayes-Mixtures

Marcus Hutter, Marcus Hutter, 2002, COLT.

On Universal Prediction and Bayesian Confirmation pdf

Marcus Hutter, Marcus Hutter, 2007, Theor. Comput. Sci..

Count-Based Exploration in Feature Space for Reinforcement Learning

Marcus Hutter, Tom Everitt, Jarryd Martin, 2017, IJCAI.

Intelligence as Inference or Forcing Occam on the World

Marcus Hutter, Peter Sunehag, 2014, AGI.

Universal Intelligence: A Definition of Machine Intelligence

Shane Legg, Marcus Hutter, S. Legg, 2007, Minds and Machines.

Probabilities on Sentences in an Expressive Logic

Marcus Hutter, John W. Lloyd, William T. B. Uther, 2012, J. Appl. Log..

Extreme state aggregation beyond Markov decision processes

Marcus Hutter, Marcus Hutter, 2016, Theor. Comput. Sci..

Context Tree Weighting

Marcus Hutter, Peter Sunehag, Marcus Hutter, 2013 .

Indefinitely Oscillating Martingales

Marcus Hutter, Jan Leike, 2014, ALT.

A Gentle Introduction to Quantum Computing Algorithms with Applications to Universal Prediction pdf

Marcus Hutter, Elliot Catt, Marcus Hutter, 2020, ArXiv.

A Universal Measure of Intelligence for Artificial Agents

Shane Legg, Marcus Hutter, 2005, IJCAI.

Axioms for Rational Reinforcement Learning pdf

Marcus Hutter, Peter Sunehag, Marcus Hutter, 2011, ALT.

Equivalence of probabilistic tournament and polynomial ranking selection

Marcus Hutter, Kassel Hingee, 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

Feature Dynamic Bayesian Networks pdf

Marcus Hutter, Marcus Hutter, 2008, ArXiv.

Feature Reinforcement Learning: State of the Art

Marcus Hutter, Peter Sunehag, Mayank Daswani, 2014, AAAI 2014.

No Free Lunch versus Occam's Razor in Supervised Learning

Tor Lattimore, Marcus Hutter, Tor Lattimore, 2011, Algorithmic Probability and Friends.

Universal Compression of Piecewise i.i.d. Sources

Marcus Hutter, Badri N. Vellambi, Cameron Owen, 2018, 2018 Data Compression Conference.

Algorithmic information theory pdf

Marcus Hutter, Marcus Hutter, 2007, Scholarpedia.

Curiosity Killed the Cat and the Asymptotically Optimal Agent pdf

Marcus Hutter, Michael K. Cohen, Michael K Cohen, 2020, ArXiv.

Matching 2-D Ellipses to 3-D Circles with Application to Vehicle Pose Estimation pdf

Marcus Hutter, Nathan Brewer, 2009, ArXiv.

Self-Modification of Policy and Utility Function in Rational Agents pdf

Marcus Hutter, Tom Everitt, Daniel Filan, 2016, AGI.

One Decade of Universal Artificial Intelligence pdf

Marcus Hutter, Marcus Hutter, 2012, ArXiv.

Reliable Point Correspondences in Scenes Dominated by Highly Reflective and Largely Homogeneous Surfaces

Hongdong Li, Marcus Hutter, Richard I. Hartley, 2014, ACCV Workshops.

A Strongly Asymptotically Optimal Agent in General Environments

Marcus Hutter, Michael K. Cohen, Elliot Catt, 2019, IJCAI.

Artificial general intelligence: Proceedings of the Second Conference on Artificial General Intelligence, AGI 2009, Arlington, Virginia, USA, March 6-9, 2009

Pascal Hitzler, Marcus Hutter, Ben Goertzel, 2009 .

A Complete Theory of Everything (Will Be Subjective) pdf

Marcus Hutter, Marcus Hutter, 2009, Algorithms.

Universal Knowledge-Seeking Agents for Stochastic Environments

Laurent Orseau, Tor Lattimore, Marcus Hutter, 2013, ALT.

Adaptive Online Prediction by Following the Perturbed Leader pdf

Marcus Hutter, Jan Poland, Marcus Hutter, 2005, J. Mach. Learn. Res..

A Formal Measure of Machine Intelligence pdf

Shane Legg, Marcus Hutter, S. Legg, 2006, ArXiv.

Feature Reinforcement Learning: Part I. Unstructured MDPs

Marcus Hutter, Marcus Hutter, 2009, J. Artif. Gen. Intell..

On the Computability of AIXI pdf

Marcus Hutter, Jan Leike, Marcus Hutter, 2015, UAI.

Towards a Universal Theory of Artificial Intelligence

Marcus Hutter, 2002 .

An effective Procedure for Speeding up Algorithms

Marcus Hutter, 2001, ArXiv.

On semimeasures predicting Martin-Löf random sequences

Marcus Hutter, Andrej Muchnik, 2007, Theor. Comput. Sci..

Sequential Decisions based on Algorithmic Probability

Marcus Hutter, Marcus Hutter, 2008 .

Sparse Adaptive Dirichlet-Multinomial-like Processes pdf

Marcus Hutter, Marcus Hutter, 2013, COLT.

Asymptotics of Continuous Bayes for Non-i.i.d. Sources pdf

Tor Lattimore, Marcus Hutter, Tor Lattimore, 2014, ArXiv.

Counterfactual Credit Assignment in Model-Free Reinforcement Learning pdf

Fabio Viola, Marcus Hutter, Nicolas Heess, 2020, ArXiv.

Compress and Control

Marc G. Bellemare, Joel Veness, Marcus Hutter, 2015, AAAI.

Tournament versus fitness uniform selection

Shane Legg, Marcus Hutter, Akshat Kumar, 2004, Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753).

Reinforcement learning with value advice

Marcus Hutter, Peter Sunehag, Mayank Daswani, 2014, ACML.

Universal Artificial Intelligence: Sequential Decisions Based on Algorithmic Probability (Texts in Theoretical Computer Science. An EATCS Series)

Marcus Hutter, Marcus Hutter, 2006 .

06051 Abstracts Collection -- Kolmogorov Complexity and Applications

Marcus Hutter, Wolfgang Merkle, Paul M. B. Vitányi, 2006, Kolmogorov Complexity and Applications.

Matching 2-D ellipses to 3-D circles with application to vehicle pose identification

Marcus Hutter, Nathan Brewer, Marcus Hutter, 2009, 2009 24th International Conference Image and Vision Computing New Zealand.

How Useful are Hand-crafted Data? Making Cases for Anomaly Detection Methods

Marcus Hutter, Len Du, 2021, HICSS.

Shaking the foundations: delusions in sequence models for interaction and control pdf

Nando de Freitas, Shane Legg, Joel Veness, 2021, ArXiv.

A rapid and efficient learning rule for biological neural circuits

Peter E. Latham, Joel Veness, Marcus Hutter, 2021 .

Intelligence and Unambitiousness Using Algorithmic Information Theory

Marcus Hutter, Badri Vellambi, Michael K. Cohen, 2021, IEEE Journal on Selected Areas in Information Theory.

Counterfactual Credit Assignment in Model-Free Reinforcement Learning

Marcus Hutter, Nicolas Heess, Fabio Viola, 2020, ICML.

Learning Curve Theory pdf

Marcus Hutter, Marcus Hutter, 2021, ArXiv.

Curiosity Killed or Incapacitated the Cat and the Asymptotically Optimal Agent

Marcus Hutter, Elliot Catt, Michael K. Cohen, 2021, IEEE Journal on Selected Areas in Information Theory.

Isotuning With Applications To Scale-Free Online Learning pdf

Laurent Orseau, Marcus Hutter, Marcus Hutter, 2021, ArXiv.

Reward-Punishment Symmetric Universal Intelligence pdf

Marcus Hutter, Samuel Allen Alexander, 2021, ArXiv.

Reducing Planning Complexity of General Reinforcement Learning with Non-Markovian Abstractions pdf

Marcus Hutter, Sultan Javed Majeed, Sultan J. Majeed, 2021, ArXiv.

Reinforcement Learning with Information-Theoretic Actuation pdf

Joel Veness, Marcus Hutter, Elliot Catt, 2021, AGI.

Fully General Online Imitation Learning pdf

Marcus Hutter, Michael K. Cohen, Neel Nanda, 2021, ArXiv.

Feature Reinforcement Learning: Part II. Structured MDPs

Marcus Hutter, 2021, J. Artif. Gen. Intell..

On the Role of Neural Collapse in Transfer Learning pdf

Marcus Hutter, Tomer Galanti, Andr'as Gyorgy, 2021, ICLR.

Family Structure from Periodic Solutions of an Improved Gap Equation

Marcus Hutter, Andreas Blumhofer, 1996 .

Instantons in QCD: Theory and Application of the Instanton Liquid Model

Marcus Hutter, Marcus Hutter, 1996, hep-ph/0107098.

Distribution of mutual information for robust feature selection

Marco Zaffalon, Marcus Hutter, 2002 .

The Alignment Problem for Bayesian History-Based Reinforcement Learners∗

Marcus Hutter, Tom Everitt, Marcus Hutter, 2019 .

The Alignment Problem for History-Based Bayesian Reinforcement Learners ∗ PUBLIC DRAFT

Marcus Hutter, Tom Everitt, Marcus Hutter, 2018 .

Model Growth

Marcus Hutter, Marcus Hutter, Jeroen van Maanen, 2002 .

Artificial general intelligence: Proceedings of the Third Conference on Artificial General Intelligence, AGI 2010, Lugano, Switzerland, March 5-8, 2010

Marcus Hutter, Emanuel Kitzelmann, Eric Baum, 2010 .

Family structure from periodic solutions of an improved gap equation

Marcus Hutter, Andreas Blumhofer, 1997 .